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Phytoplankton chlorophyll distributions and primaryproduction in the Southern Ocean

J. Keith Moore1 and Mark R. AbbottCollege of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis

Abstract. Satellite ocean color data from the Sea-viewing Wide Field-of-view Sensor(SeaWiFS) were used to examine distributions of chlorophyll concentration within theSouthern Ocean for the period October 1997 through September 1998. Over most of theSouthern Ocean, mean chlorophyll concentrations remained quite low (,0.3–0.4 mg m23).Phytoplankton blooms where chlorophyll concentration exceeded 1.0 mg m23 wereobserved in three general areas, which included coastal/shelf waters, areas associated withthe seasonal sea ice retreat, and the vicinity of the major Southern Ocean fronts. Thesechlorophyll distribution patterns are consistent with an iron-limited system. Meanchlorophyll concentrations from SeaWiFS are compared with values from the coastal zonecolor scanner (CZCS). The SeaWiFS global chlorophyll algorithm works better than theCZCS in Southern Ocean waters. Primary production in the Southern Ocean wasestimated with the vertically generalized production model of Behrenfeld and Falkowski[1997]. Annual primary production in the Southern Ocean (.308S) was estimated to be14.2 Gt C yr21, with most production (;80%) taking place at midlatitudes from 308 to508S. Primary production at latitudes .508S was estimated to be 2.9 Gt C yr21. This isconsiderably higher than previous estimates based on in situ data but less than somerecent estimates based on CZCS data. Our estimated primary production is sufficient toaccount for the observed Southern Hemisphere seasonal cycle in atmospheric O2concentrations.

1. Introduction

Phytoplankton bloom dynamics in the Southern Ocean havelong represented a paradox for oceanographers. Despite highconcentrations of available nitrate and phosphate, chlorophyllconcentrations in open ocean waters remain low (typically,0.5 mg m23) [Treguer and Jacques, 1992; Comiso et al., 1993;Banse, 1996]. The Southern Ocean is thus the largest high-nutrient low-chlorophyll (HNLC) region in the world ocean[Martin, 1990; Minas and Minas, 1992]. In recent years, sub-stantial evidence has accumulated that the availability of themicronutrient iron plays a critical role in limiting phytoplank-ton biomass and production within HNLC regions [Martin etal., 1990a, 1990b; de Baar et al., 1995; Coale et al., 1996; Gordonet al., 1997; van Leeuwe et al., 1997; Takeda, 1998].

There have been several satellite-based studies of SouthernOcean phytoplankton dynamics that relied on data from thecoastal zone color scanner (CZCS). Arrigo and McClain [1994]used CZCS data to estimate primary production in the RossSea. Several studies combined CZCS data with satellite-derived ice cover information to examine ice edge phytoplank-ton bloom dynamics [Sullivan et al., 1988; Comiso et al., 1990].

Comiso et al. [1993] examined CZCS pigment data for theentire Southern Ocean and analyzed their relationship to sev-eral geophysical features. They noted that phytoplanktonblooms occur primarily in several regions including areas as-

sociated with sea ice retreat, shallow waters, areas of strongupwelling, and regions of high eddy kinetic energy (mainlyassociated with Southern Ocean fronts) [Comiso et al., 1993].The strongest correlation with pigments was a negative corre-lation between ocean depth and pigment concentrations, pos-sibly the result of higher available iron concentrations in shal-low water regions [Comiso et al., 1993]. Sullivan et al. [1993]also examined CZCS pigment data for the whole SouthernOcean. They noted intense phytoplankton blooms within anddownstream of coastal/shelf areas, which they attributed toelevated iron availability [Sullivan et al., 1993]. Silicic acidavailability may limit diatom production and biomass accumu-lation in several areas [Treguer and Jacques, 1992; Sullivan etal., 1993]. Mitchell and Holm-Hansen [1991] developed a re-gional Southern Ocean pigment (SOP) retrieval algorithm forthe CZCS on the basis of the bio-optical properties of Antarc-tic Peninsula waters. This regional pigment algorithm wasdeemed necessary because the global pigment (GP) algorithmfor CZCS [Gordon et al., 1983] resulted in underestimates ofsurface chlorophyll concentrations in Southern Ocean waters[Mitchell and Holm-Hansen, 1991; Sullivan et al., 1993; Arrigo etal., 1994]. Arrigo et al. [1994] provided correction factors forconverting GP pigment estimates to SOP pigment values. TheSOP pigment values are higher than the GP estimates by afactor ranging from ;2.1 to 2.5 for chlorophyll concentrationsbelow 1.5 mg m23 [Arrigo et al., 1994].

In this study, Sea-viewing Wide Field-of-view Sensors(SeaWiFS) satellite-based estimates of surface chlorophyllconcentrations are used to examine phytoplankton biomassdistributions and dynamics within the Southern Ocean. We usea broad definition for the Southern Ocean encompassing thearea from the Antarctic continent north to 308S. This northern

1Now at Advanced Studies Program, National Centers for Atmo-spheric Research, Boulder, Colorado.

Copyright 2000 by the American Geophysical Union.

Paper number 1999JC000043.0148-0227/00/1999JC000043$09.00

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 105, NO. C12, PAGES 28,709–28,722, DECEMBER 15, 2000

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boundary is ;58 of latitude north of the mean position of theNorth Subtropical Front as defined by Belkin and Gordon[1996]. Technically, the North Subtropical Front marks thenorthern border of the Southern Ocean. The 308S boundary isused to encompass northern meanders of this front. Meanlatitude in the Indian sector of the North Subtropical Front isas far north as 328–338S [Belkin and Gordon, 1996].

Primary production in the Southern Ocean is estimated us-ing the vertically generalized production model (VGPM) ofBehrenfeld and Falkowski [1997]. Satellite-derived estimates ofsurface chlorophyll, sea surface temperature, sea ice cover, andsurface photosynthetically available radiation are used to drivethis model. Our results are compared with several recent stud-ies that used data from the CZCS to model primary productionin Southern Ocean waters [Longhurst et al., 1995; Behrenfeldand Falkowski, 1997; Arrigo et al., 1998] as well as with esti-mates extrapolated from in situ measurements. We also com-pare our estimates of total primary production with estimatesof seasonal net production based on atmospheric O2 variations[Bender et al., 1996].

2. Methods and MaterialsSeaWiFS-derived estimates of surface chlorophyll concen-

trations for the period October 1997 through September 1998were obtained from the Goddard Space Flight Center [Mc-Clain et al., 1998]. Daily level 3 standard mapped images ofchlorophyll concentration (version 2) were composite-averaged to produce weekly, monthly, seasonal, and annualmeans for the Southern Ocean. We compare these SeaWiFSestimates with data from the CZCS. Monthly CZCS compos-ites processed with the global algorithm (GP) [Gordon et al.,1983] over the 1979–1986 period were obtained from NASA.We also derived monthly CZCS composites based on theSouthern Ocean pigment (SOP) algorithm [Mitchell and Holm-Hansen, 1991] using the correction factors of Arrigo et al.[1994].

Monthly mean sea ice concentrations (NASA Team algo-rithm) from the Special Sensor Microwave Imager (SSM/I)DMSP-F13 satellite sensor for the years 1997–1998 were ob-tained from the Earth Observing System Data and InformationSystem (EOSDIS) National Snow and Ice Data Center(NSIDC) Distributed Active Archive Center, University ofColorado, Boulder [National Snow and Ice Data Center, 1998].Ice concentrations of ,5% were considered to be open waterin our analysis. A minimum of 70% ice cover was used todetermine the minimum (summer) sea ice extent. This valuewas chosen because significant phytoplankton biomass can ac-cumulate in the water column at ice concentrations below;70% [e.g., Smith and Gordon, 1997]. All sea ice data wereremapped to a 9 km equal angle grid.

The satellite chlorophyll data were analyzed by ecologicalregion within the Southern Ocean. We divide the SouthernOcean into several ecological regions, including the Midlati-tude Gyre Region (MGR), the Midlatitude Coastal Region(MCR), the Subantarctic Water Ring (SWR), the Polar Fron-tal Region (PFR), the Permanently Open Ocean Zone(POOZ), the Seasonal Ice Zone (SIZ), the Marginal Ice Zone(MIZ), and the Weddell-Ross Region (WRR). From the Ant-arctic Polar Front south to Antarctica these ecological regionsare similar to those proposed by Treguer and Jacques [1992].The WRR consists of the waters of the Weddell and Ross Seasthat are south of 738S. This region is similar to the Coastal and

Continental Shelf Zone of Treguer and Jacques [1992]. The SIZis defined as areas with .5% ice cover during August 1997(maximum ice extent prior to growing season) and less ,70%ice cover during February 1998 (seasonal minimum ice extent).The MIZ is a subset of the SIZ where there has been recentmelting of sea ice [Smith and Nelson, 1986]. We operationallydefine this ecologically important region as areas with .50%sea ice cover the preceding month and ,50% ice cover in thecurrent month. Previously, we have used 70% ice cover todefine MIZ [Moore et al., 2000]. Here we use 50% to includethose areas that begin the growing season at ,70% ice cover.A wide range of cutoff values can be used in determining theMIZ (;30–70%) that give similar results because sea ice meltsrapidly in the Southern Ocean, typically going from heavy tolittle ice cover in less than a month. The PFR is defined as allareas within 18 of latitude of the mean path for the AntarcticPolar Front (PF) as defined by Moore et al. [1999a]. Thislocation of the PF is based on satellite sea surface temperaturedata and thus marks the surface expression of the front. ThePF has both surface and subsurface expressions [see Moore etal., 1999a]. Arguably, the surface expression has a strongerinfluence on the biota and is thus appropriate for use here. Inany case the mean locations of the front based on surface andsubsurface definitions are quite similar in most regions [Mooreet al., 1999a]. The POOZ is the area north of the SIZ and southof the PFR.

The SWR is defined as the area from the PFR north to theSubtropical Fronts [Banse, 1996]. The northern border of thisregion is set at 358S, slightly north of the mean position of theNorth Subtropical Front as defined by Belkin and Gordon[1996]. North of this region, are the mid-ocean gyre systems ofthe Southern Hemisphere. This area, 308–358S, we term theMGR. To define open ocean patterns better we have excludedareas shallower than 500 m from the MGR, SWR, PFR, andPOOZ areas using the topography data of Smith and Sandwell[1994]. These shallow coastal and shelf areas are collectivelyreferred to as the MCR.

There is some overlap between these ecological regions. TheWRR and the MIZ are subsets of the SIZ. We have excludedthe WRR areas from the MIZ and SIZ. In the southwestPacific and through Drake Passage the SIZ and MIZ overlapwith the PFR. These areas have been included only within ourSIZ and MIZ regions, and thus are excluded from the PFR.

Chlorophyll distributions are also compared with the meanpositions of the major Southern Ocean fronts. We have usedthe mean path of Moore et al. [1999a] for the Antarctic PF. Thepositions of the Southern Antarctic Circumpolar CurrentFront (SACCF) and the Subantarctic Front (SAF) are fromthe analysis of Orsi et al. [1995]. The locations of the NorthSubtropical Front (NSTF) and South Subtropical Front(SSTF) and the Agulhas Current are from Belkin [1993, 1988]and Belkin and Gordon [1996]. The region from the SSTF tothe NSTF is termed the Subtropical Frontal Zone (STFZ)[Belkin and Gordon, 1996]. The terminology and abbreviationsused in defining the ecological regions and fronts are summa-rized in Table 1.

3. Modeling Primary ProductionPrimary production over monthly timescales was estimated

using the VGPM [Behrenfeld and Falkowski, 1997]. The inputsto the VGPM are satellite-derived surface chlorophyll concen-trations, sea surface temperatures, and photosynthetically


available radiation (PAR) at the water’s surface [Behrenfeldand Falkowski, 1997]. Photoperiod, or day length, is calculatedas a function of latitude and time of year. Monthly optimallyinterpolated sea surface temperature (SST) data at 18 resolu-tion were obtained from the National Centers for Environmen-tal Prediction for the October 1997 to September 1998 period[Reynolds and Smith, 1994]. The SST data were remapped to a9 km equal angle grid using linear interpolation between gridpoints.

The SST data are used to estimate the local maximum rateof primary production (Popt

B ) in the model according to thePopt

B versus SST regression of Behrenfeld and Falkowski [1997].This empirical function is valid only for SST values from 218 to298C. For areas where SST was ,21.08C, Popt

B was set to the21.08C value (1.1 mg C (mg Chl)21 h21), and for SST above298C, Popt

B was set to the 29.08C value (3.8 mg C (mg Chl)21

h21). In the SST data set, there often were no valid SST dataat very high latitudes, mainly in the southern Weddell and RossSeas. An SST value of 21.08C was used for computing primaryproduction in these areas. Examination of the Pathfinder Pro-gram SST data set [Smith et al., 1996] revealed that mean SSTvalues were below 21.08C in these areas during our studyperiod.

Monthly surface PAR data for the years 1983–1984 wereobtained from the SeaWiFS Project, and the data from the 2years were averaged to produce a monthly mean (cloud-corrected) surface PAR, which was remapped to a 9 km equalangle grid with linear interpolation between grid points. Totalwater column chlorophyll was estimated from the satellitechlorophyll data using the equations of Morel and Berthon[1989]. Equation (3a) of Morel and Berthon [1989] was used forareas equatorward of 508S, and for latitudes $508S (well-mixedwaters) we used Morel and Berthon [1989, equation (5)]. Totalwater column chlorophyll was then used to estimate euphoticdepth using Morel and Berthon [1989, equations (1a) and (1b)].

Two types of gaps were present in the monthly chlorophyllcomposites used to drive the primary production model. A

small number of pixels had no data because of persistent cloudcover for the entire month. A second larger gap appears in thechlorophyll data at high latitudes seasonally because of theshort day length and the inability of SeaWiFS to produceaccurate chlorophyll estimates at very high solar angles. Forthis reason, there are little or no SeaWiFS data south of ;458–508S during austral winter. These gaps must be removed insome manner to avoid underestimating total primary produc-tion. There is high spatial variability in chlorophyll concentra-tions within the Southern Ocean. For this reason we havechosen to smooth the data over time rather than space. Wetreat the area equatorward of 408S (weak seasonality) differ-ently than the area poleward of 408S (strong seasonality). Gapsin the data equatorward of 408S were filled with the annualmean chlorophyll value over the October 1997 to September1998 time period.

For the data gaps at latitudes $408S we first averaged themonthly data from March and September 1998. The compositeof these 2 months was then used to fill data gaps. DuringMarch and September (late fall and early spring) phytoplank-ton biomass (and chlorophyll concentrations) is low, and thesystem is likely light-limited. Using the composite of these 2months thus represents a conservative method to fill in chlo-rophyll gaps that will not result in an overestimate of primaryproduction. Most of the gaps filled were the seasonal typedescribed above and occurred during austral winter. The fewremaining gaps after this two-step process were filled by aver-aging all adjacent pixels with valid chlorophyll data. To preventextending the chlorophyll data into areas with heavy sea icecover (where primary production is negligible), we comparedthe smoothed monthly chlorophyll data with the monthly seaice data and removed chlorophyll data in areas where sea iceconcentration exceeded 70%. The smoothed chlorophyll fieldswere used only in the calculations of primary production. Allother analyses are based upon the original monthly compositesof the level 3 chlorophyll data.

We estimate area-normalized production using two meth-ods. In the first the mean production per square meter iscalculated for all productive waters in a given region overmonthly timescales. Productive waters are those with ,70%sea ice cover with some light available (during winter months)for primary production. The method gives results similar towhat repeated ship surveys to the region would find and isprobably the better value for cross-study comparisons. In thesecond method we divide the total production by the total areaof a given region. This total area includes both productive andnonproductive waters and thus results in lower estimates ofarea-normalized production.

4. Results4.1. Satellite-Based Estimates of Chlorophyll in theSouthern Ocean

Several previous studies argued that the global processingalgorithm (GP) used for the CZCS consistently underesti-mated surface chlorophyll concentrations in the SouthernOcean [Mitchell and Holm-Hansen, 1991; Sullivan et al., 1993;Arrigo et al., 1994]. An early comparison of a limited in situdata set from the Polar Frontal region near 1708W, 608S withSeaWiFS data (N 5 84) indicates generally good agreementbetween satellite and in situ measurements (r2 5 0.72, froma linear regression of shipboard versus satellite data) but alsothat the SeaWiFS algorithm (OC2) may underestimate abso-

Table 1. Abbreviations Used for the Various SouthernOcean Ecological Regions and Ocean Fronts

Abbrev-iation Definition

Ecological RegionsWRR Weddell-Ross Region, high-latitude Weddell and Ross SeasSIZ Seasonal Ice Zone, .5% ice cover August 1997 and ,70%

ice cover February 1998MIZ Marginal Ice Zone, .50% ice cover in preceding month

and ,50% in current monthPOOZ Permanently Open Ocean Zone, north of SIZ and south

of PFRPFR Polar Frontal Region, area within 18 latitude of Antarctic

Polar Front mean locationSWR Subantarctic Water Ring, area north of PFR to 358SMGR Midlatitude Gyre Region, area from 308 to 358SMCR Midlatitude Coastal Region, areas in MGR, SWR, PFR,

and POOZ, where depth ,500 m

Ocean FrontsSACCF Southern Antarctic Circumpolar Current FrontPF Antarctic Polar FrontSAF Subantarctic FrontSSTF South Subtropical FrontNSTF North Subtropical FrontAC Aghulas Current


lute Southern Ocean (SO) chlorophyll concentrations, al-though to a lesser extent than the CZCS [Moore et al., 1999b].The SO pigment algorithm (SOP) was developed for CZCSdata and resulted in chlorophyll concentrations higher than inthe GP algorithm [Mitchell and Holm-Hansen, 1991].

To examine how well SeaWiFS is estimating chlorophyllconcentrations in the SO, we compared mean chlorophyll con-centrations from SeaWiFS with the CZCS data processed withthe GP algorithm and with the SOP-corrected values (Table 2).Monthly means were composite-averaged over the October toMarch period. Mean chlorophyll concentrations were calcu-lated for several latitudinal bands (Table 2). CZCS mean pig-ment values were converted to chlorophyll using a mean chlo-rophyll/phaeopigment ratio of 2.57 from Arrigo et al. [1994],which was calculated from an extensive in situ SO data set(N 5 1070). As in previous averaging of CZCS data bySullivan et al. [1993], we excluded areas of chlorophyll (orpigment) concentration .10.0 mg m23 (a small percentage ofthe total pixels, always ,0.43%).

Several lines of evidence argue that the SeaWiFS globalchlorophyll algorithm is doing a better job of estimating SOchlorophyll concentrations than was the CZCS. Table 2 shows

that the SeaWiFS estimates for mean surface chlorophyll con-centrations over all latitudinal bands lie between the CZCS GPand SOP estimates. These values can be compared with severalmeans compiled from in situ data. Banse [1996] compiled anumber of in situ data sets and estimated a seasonal peakwithin the SWR of ;0.30 mg m23. This is in good agreementwith our mean October–March concentration of 0.29 mg m23

for the 358–508S region (Table 2) and a mean SWR Decembervalue of 0.30 mg m23 (Plate 5). Fukuchi [1980] estimated meanchlorophyll concentrations over the latitudinal range 358–638Sto be 0.38 (east Indian sector December), 0.23 (west Indiansector late February/early March), and 0.27 mg m23 (eastAtlantic sector late February/early March). These valuesbracket the mean October–March SeaWiFS estimates (Table2). The compilation of in situ data by Arrigo et al. [1994]estimated mean chlorophyll south of 308S to be 0.42 mg m23

(0.58 mg m23 total pigments and a chlorophyll/phaeopigmentratio of 2.57). This value is higher than the SeaWiFS estimatebut lower than the CZCS SOP estimate for latitudes .308S(Table 2).

The irregular temporal and spatial coverage of the in situdata likely bias mean in situ chlorophyll concentrations up-ward. Since chlorophyll concentrations tend to increase withlatitude (Table 2), simple averaging over a latitudinal shiptransect with regular spatial sampling would underestimate thetotal contribution from low-chlorophyll (Subantarctic) waterswhile giving equal weight to waters farther south (which aremuch smaller in their spatial extent, see Table 3). In addition,many in situ studies have focused on the biologically produc-tive marginal ice zone where chlorophyll concentrations aremuch higher than SO averages (Plate 5 and Table 2). Thedistribution of in situ samples used by Arrigo et al. [1994] isweighted toward samples from .508S in the Atlantic and In-dian sectors, with fewer samples from Subantarctic waters (thegenerally high-chlorophyll waters near New Zealand are wellsampled) [see Arrigo et al., 1994, Figure 21]. This partiallyaccounts for the higher mean chlorophyll concentration of 0.42mg m23 [Arrigo et al., 1994].

By comparing the in situ values with the estimates fromTable 2 it is evident that the CZCS GP algorithm did seriously

Table 2. Mean Chlorophyll Concentrations for AustralSpring/Summer Months (October–March) Over SeveralLatitudinal Bandsa

SeaWiFS,mg m23

CZCS (GP),mg m23

CZCS (SOP),mg m23

358–508S 0.29 0.15 (0.21) 0.37 (0.52)508–908S 0.35 0.28 (0.39) 0.58 (0.81)358–908S 0.34 0.22 (0.31) 0.49 (0.69)308–908S 0.30 0.21 (0.29) 0.45 (0.63)

aCZCS pigment values were computed with the original global chlo-rophyll algorithm (GP) [Gordon et al., 1983], and then the data werecorrected to reflect the Southern Ocean Pigment (SOP) algorithm[Mitchell and Holm-Hansen, 1991] using the correction factors of Arrigoet al. [1994] before averaging. CZCS mean pigment values (shown inparentheses) were converted to chlorophyll using a mean chlorophyll/phaeopigment ratio of 2.51 [Arrigo et al., 1994]. All values exceeding10.0 mg m23 were excluded during averaging.

Table 3. Annual Primary Production Estimates Using the VGPM Model of Behrenfeldand Falkowski [1997]a

Region

ProductiveWaters,

gC m22 yr21All Waters,

gC m22 yr21Total Area,million km2

TotalProduction,Gt C yr21

MGR 145.3 145.3 15.3 (14.1) 2.22 (15.7)MCR 528.8 505.8 2.57 (2.4) 1.30 (9.2)SWR 161.2 159.7 58.0 (53.6) 9.26 (65.4)PFR 82.0 73.2 4.89 (4.5) 0.385 (2.7)POOZ 62.3 58.5 8.70 (8.0) 0.509 (3.6)SIZ 50.8 29.1 16.2 (15.0) 0.472 (3.3)WRR 156.2 58.4 0.95 (0.88) 0.0555 (0.39)Southern Ocean

(308–908S)148.5 131.0 108.2 (100) 14.17 (100)

Southern Ocean(508–908S)

82.2 62.4 45.7 (42.2) 2.85 (20.1)

MIZ 54.2 0–5.53 (0–5.1) 0.096 (0.67)

aThe percentage of total Southern Ocean primary production and ocean area accounted for is shown inparentheses for each region. Area-normalized production is calculated in two ways. The mean of allproductive waters (,70% ice cover and some light available for photosynthesis) was calculated monthlyand then summed (column 1). For calculating column 2, total production was divided by total area, whichincludes nonproductive waters (waters with .70% ice cover or no light during austral winter).


underestimate chlorophyll concentrations in the SouthernOcean [Mitchell and Holm-Hansen, 1991; Sullivan et al., 1993;Arrigo et al., 1994]. In contrast, the CZCS SOP algorithmvalues are higher than the in situ means. There is reason tobelieve that the CZCS SOP algorithm may have overestimatedpigment concentration at low pigment concentrations. Arrigo etal. [1994] and Sullivan et al. [1993] compared CZCS data pro-cessed with the GP and SOP algorithms with a large in situdata set averaged over 18 latitudinal bands. Both algorithmsexplained 71% of the variance seen in the in situ data set, withthe SOP algorithm performing much better at higher pigmentconcentrations (.;0.6 mg m23) [Sullivan et al., 1993]. How-ever, a regression of the SOP algorithm estimates of surfacepigment versus in situ data had the equation y 5 0.16 10.905x [Sullivan et al., 1993]. The large y offset of 0.16 mg m23

implies that the SOP algorithm may substantially overestimatepigment concentrations at lower chlorophyll (pigment) values(,;0.6 mg m23, i.e., by 50% where chlorophyll is 0.32 mgm23). Since over most of the SO chlorophyll concentrations donot exceed 0.6 mg m23, use of the SOP algorithm may signif-icantly overestimate chlorophyll concentration over much ofthe Southern Ocean. The SOP algorithm was developed froma data set from Antarctic Peninsula waters, with no total pig-ment values ,0.5 mg m23 [Mitchell and Holm-Hansen, 1991].In addition to the relatively high pigment values in AntarcticPeninsula waters, species-related pigment packaging effects inthis region may not be representative of the whole SO. Somephytoplankton species such as Phaeocystis spp. are commonlyfound near the Antarctic Peninsula but typically are a minorcomponent of the assemblages farther north. Thus applicationof this algorithm to all SO waters, particularly to low-chlorophyll Subantarctic waters, may overestimate chlorophyllconcentrations. This highlights the problems with regionalchlorophyll algorithms: namely, over what area should they beapplied and how is the transition between regions managed?

In general, the SeaWiFS estimates are in better agreementwith the in situ data than either CZCS data set. In part, thislikely reflects the better temporal and spatial coverage by Sea-WiFS. The largest gaps in the CZCS coverage occur in thelow-chlorophyll waters of the Pacific sector [Comiso et al.,1993]. Large areas with no valid chlorophyll data also occur inthe Indian sector (generally, a low-chlorophyll area; see Plates1 and 3) during most austral summer monthly composites[Comiso et al., 1993]. These gaps may partially account for thehigher mean values in the CZCS SOP data set. The goodagreement between SeaWiFS and the in situ data arguesstrongly that the global chlorophyll algorithm is working well inthe SO and, at least for Subantarctic waters, a regional algo-rithm is not necessary. At higher latitudes, SeaWiFS may beunderestimating chlorophyll concentrations, although to alesser extent than did the CZCS (Table 2) [Moore et al., 1999b].

4.2. Chlorophyll Distributions in the Southern Ocean

Monthly mean chlorophyll concentrations during australspring and summer are shown in Plate 1 (areas in black had novalid chlorophyll data because of heavy sea ice or persistentcloud cover). Over most of the Southern Ocean, mean chlo-rophyll concentrations remain low despite the available nitrateand phosphate in surface waters (typically ,0.3–0.4 mg m23,Plate 1). Very low chlorophyll values are seen north of ;358Swithin the subtropical gyres, in the southern half of DrakePassage (;808–608W), and along ;608–658S between 208 and708E. This last area of low chlorophyll along 608S marks the

location of the Antarctic Divergence (AD), where strong up-welling occurs as a result of wind-driven divergence of surfacewaters [see Comiso et al., 1993]. This upwelling is clearly seenin oxygen concentrations at 100 m depth [Gordon et al., 1986].The recent upwelling of these waters may account for thelow-chlorophyll values observed in this area. Relatively lowchlorophyll concentrations are also seen in the Indian sector;1008–1308E at similar latitudes (Plate 1b) in another regionof high winds and strong upwelling during austral summer[Comiso et al., 1993].

Phytoplankton blooms with chlorophyll values exceeding 1.0mg m23 are seen in several areas. The highest values occur incoastal and shelf waters associated with Southern Ocean is-lands and continents. Thus high-chlorophyll values are seensurrounding and downstream of Kerguelen Island (;508S,708E), over the large shelf region on the east coast of SouthAmerica, and in shelf regions associated with Africa, Australia,and New Zealand. High-chlorophyll values are also seen in thesouthern Weddell and Ross Seas and in other coastal Antarcticwaters.

Monthly percentage sea ice cover for the November 1997 toFebruary 1998 period is shown in Plate 2. During Novemberthe sea ice cover was still near its maximal winter extent overmost of the Southern Ocean. There was a rapid melting of theseasonal sea ice cover during December and January (Plate 2).Most of this seasonal retreat of the sea ice cover occurs in theWeddell and Ross Seas (Plate 2). By comparing Plates 1 and 2,it can be seen that large phytoplankton blooms occur in areaswhere the sea ice has retreated in the Weddell Sea (;0–308W,below ;608S). Similar phytoplankton blooms are apparent inthe Ross Sea ;1508–1758W, below ;608S during Decemberand below ;658S during January and February (comparePlates 1 and 2). It is important to note that phytoplanktonblooms do not occur in all areas of sea ice retreat (comparePlates 1 and 2). For example, chlorophyll values remain verylow between ;108–608E and 608–658S despite the retreat ofsea ice here over the November–January period (comparePlates 1 and 2). In other areas where ice cover is retreating,including parts of the Weddell and Ross Seas, chlorophyllconcentrations also remain quite low (,0.3 mg m23). Possiblecauses for these variations in ice edge bloom dynamics includevariations in wind speed (and thus mixed layer depth), differ-ential accumulation of atmospheric dust on the ice (whichaffects the amount of iron released to the water column duringmelting), and differences in Ekman-induced upwelling/downwelling by the winds.

A large polynya opened in the southern Weddell Sea duringearly austral spring (Figures 2a and 2b). This early melting andconsequent low summer ice extent in the southern WeddellSea is very unusual [see Comiso and Gordon, 1998] and had astrong influence on the biota. A strong phytoplankton bloomdeveloped within the polynya, which eventually encompassedthe entire southern Weddell Sea (at latitudes .708S in the westand .;738S in the east; Plates 1 and 3). Analysis of weeklymaps of chlorophyll concentration and sea ice cover in thisregion indicates that this phytoplankton bloom developed assoon as the polynya opened up and persisted until the ninthweek of 1998 when heavy sea ice cover rapidly covered theregion. Comiso et al. [1990] also observed high chlorophyllconcentrations persisting into March in the Weddell Sea withthe CZCS. Reflection of light from ice- and snow-coveredareas may bias the SeaWiFS data near the coast (within ;50


km). However, the large size of this bloom in the southernWeddell Sea precludes its being an artifact of this type.

The remaining areas of high-chlorophyll values present inthe monthly composites shown in Plate 1 are associated withthe major fronts of the Southern Ocean. This is illustrated inPlate 3 where mean chlorophyll for the period December 1997to February 1998 is shown along with the mean position of themajor Southern Ocean fronts. Moving from high to low lati-tudes, the fronts depicted include the SACCF, the PF, theSAF, and the SSTF and NSTF. Also depicted in the regionsouth of Africa is the Agulhas Current (AC).

Frontal-associated phytoplankton blooms at higher latitudesoften occur in regions where the fronts interact with largetopographic features [Moore et al., 1999b]. Thus persistentphytoplankton blooms are seen at the SACCF where it followsthe Southeast Indian and Pacific-Antarctic Ridges (;1608E–1458W) and along the Mid-Atlantic Ridge (;58–308E) (Plate3). Likewise, blooms at the PF can be seen along the Pacific-Antarctic Ridge (especially ;1458–1608W), at the FalklandPlateau (;488–388W), and along the Mid-Atlantic Ridge(;208W–308E).

Mesoscale physical-biological interactions where SouthernOcean fronts interact with topography can stimulate phyto-plankton blooms [Moore et al., 1999b]. Two physical processescan result in an increased nutrient flux from subsurface watersto the surface layer in these regions. Vertical mixing may beincreased by eddy actions as relative vorticity added to thewater column by the large changes in ocean depth is dissipated[Moore et al., 1999b]. Second, in these regions of strong topo-graphic interaction and just downstream, mesoscale meander-ing of the PF is intensified (at spatial scales ,100 km) [Mooreet al., 1999a, 1999b]. Such meandering leads to localized areasof upwelling and downwelling, which can strongly influenceocean biota [Flierl and Davis, 1993]. In addition, cross-frontalmixing could stimulate phytoplankton growth if different nu-trients are limiting growth north and south of a particularfront. For example, there is often a strong gradient in silicicacid concentrations across the PF, resulting in silica limitationof diatom growth to the north and, perhaps, iron limitation tothe south [Treguer and Jacques, 1992; Comiso et al., 1993].Likewise, in the subtropical frontal region, nitrate availabilitylikely limits phytoplankton growth rates in the gyre regions tothe north, while iron limitation is more likely to the south[Sedwick et al., 1997].

Phytoplankton blooms at the SAF, SSTF, and NSTF areapparent in the Atlantic and Indian sectors but are generallylacking in the Pacific sector. Iron inputs at midlatitudes fromatmospheric deposition are much lower in the Pacific com-pared with the Atlantic and Indian Oceans [Duce and Tindale,1991]. Phytoplankton blooms are apparent in the vicinity of theSAF in the southeast Pacific during December 1997 (Plates 1band 3). This is notable because phytoplankton blooms were notobserved in this region with the CZCS sensor [Sullivan et al.,1993; Comiso et al., 1993].

Intense, persistent phytoplankton blooms are also associatedwith the AC and the SSTF in the African sector (;208–708E)(Plates 1 and 3). The AC is influenced by topographic featuresin this region and interacts with, and at times merges with, theSSTF and the SAF [see Belkin and Gordon, 1996]. Comiso et al.[1993] also noted high chlorophyll values in this region. Theyattributed these phytoplankton blooms to the high eddy kineticenergy and possible current-induced upwelling in this region[Comiso et al., 1993].

One way to quantify these chlorophyll distributions is todivide the Southern Ocean into ecological regions. The MIZcovered a large area during December (5.5 million km2) andJanuary (4.3 million km2). The location and shape of the MIZchanges considerably from month to month during the spring/summer period (Plates 4b and 4c). The size of the MIZ wasnegligibly small over most of the rest of the year, reaching aminimum during May 1998 (,1800 km2).

Monthly mean chlorophyll concentrations within these eco-logical regions are displayed in Plate 5. Maximum chlorophylllevels were observed in the southern Weddell and Ross Seas,with a peak value of 5.5 mg m23 during December 1997. Highchlorophyll values were also observed in the MCR and withinthe MIZ. Mean chlorophyll values remained persistently low inthe other regions, typically below 0.3 mg m23 (although thePFR reached 0.43 mg m23 during December; Plate 5).

Most regions showed a seasonal peak in chlorophyll concen-tration during December in phase with the seasonal solar ra-diation cycle. Exceptions to this pattern include the MCR,where little seasonality was observed, and the MGR, wherethere was an inverse pattern, with a minimum during australsummer. The seasonal pattern within the MGR is similar tothat observed in the North Central Pacific Gyre at stationALOHA [Letelier et al., 1993]. In that region the seasonal cycleis primarily due to photoadaptation, with chlorophyll per cellin the surface layer increasing during winter months [Letelier etal., 1993]. Another possibility would be increased nutrient in-put (and phytoplankton biomass) during winter months in theMGR because of deeper wind mixing. The SIZ and MIZ re-gions had peak mean chlorophyll values in January and Feb-ruary, respectively (Plate 5).

4.3. Primary Production in the Southern Ocean

Primary production within the Southern Ocean, summedover seasonal timescales, as estimated with the VGPM isshown in Plate 6. The highest production occurs during australsummer, with maximum values in the coastal/shelf waters off ofSouth America, Africa, Australia, and New Zealand and in thesouthern Weddell and Ross Seas (Plate 6b). Elevated produc-tion is also seen in the STFZ during all seasons in the Atlanticand Indian sectors and, to a much lesser extent, in the Pacificsector (compare Plates 3 and 6). This high primary productionreflects the generally elevated chlorophyll values within theSTFZ in the Atlantic and Pacific basins, combined with favor-able SSTs (see discussion below) (Plates 1, 2, and 6).

At high latitudes, heavy sea ice cover and the seasonal in-solation cycle lead to strong light limitation and negligibleprimary production below 608S during austral winter (Plate6d). The effect of sea ice distribution is also apparent duringaustral spring (compare Plates 2a and 6a). Some productionoccurs within the seasonal ice zone during austral fall prior tothe seasonal sea ice expansion (Plate 6c). North of these high-latitude areas, significant primary production occurs during allseasons (Plate 6).

We next examine seasonal primary production patternswithin the ecological regions described. Production per unitarea was calculated using method 1, averaging all pixels withsome production in a given region (i.e., ice cover ,70% andsome light available during winter months; Plate 7). Primaryproduction per unit area was highest in the coastal/shelf areasof the WRR and MCR (Plate 7). All regions except the MGRshow maximum production during austral summer, with the


amplitude of this seasonal cycle increasing sharply with in-creasing latitude (Plate 7).

SST has a strong impact on the model estimates of primaryproduction by setting the local maximum rate of primary pro-duction [Behrenfeld and Falkowski, 1997]. Within the low-chlorophyll regions, there is a latitudinal trend with the high-latitude (cold SST) regions having lower primary productionvalues than regions farther north (warmer SST values) (Plate7). Thus, despite having higher biomass the SIZ and MIZregions generally have lower area-normalized production ratesrelative to the other regions (compare Plates 5 and 7). Thistemperature effect also accounts for the moderately high pro-duction values within the SWR despite generally low chloro-phyll concentrations (Plates 5 and 7). Likewise, the warm SSTvalues associated with the midlatitude gyres partially make upfor the very low biomass/chlorophyll concentrations in thisregion (Plates 5 and 7). Finally, comparing the two coastalregions, the warmer SST values in the MCR raise productionvalues here to higher levels than in the cooler but higherchlorophyll waters of the WRR (Plates 5 and 7).

If we examine total primary production by ecological region,it is apparent that the SWR accounts for most of the produc-tion within the SO because of its large areal extent and mod-erately high primary production during all seasons (Plate 8). Aweak seasonal cycle is seen in the MCR and MGR regions, anda strong seasonal cycle is apparent with increasing latitude.Despite its high chlorophyll levels and primary productionvalues the total carbon fixed within the WRR is small becauseof a relatively small spatial extent.

Annual primary production estimates for the various eco-logical regions of the SO are summarized in Table 3. Alsoshown in Table 3 are the percentages of the total SO primaryproduction and area accounted for by each subregion. Notethat area values in Table 3 are the maximum total area beforecorrecting for sea ice cover and for complete light limitation athigh latitudes during austral winter. For example, note that thetotal area below 508S is 45.7 million km2; however, the maxi-mum area over which the model was run was 41.3 million km2

(during February 1998, minimum ice extent), similar to previ-ous studies [see Arrigo et al., 1998]. Annual area-normalizedproduction was calculated by the two methods described insection 2. Total production (column 3) was calculated by sum-ming the monthly production maps.

Note that the effective growing season for phytoplanktondeclines from 12 months per year at low latitudes to ,6months per year at the highest latitudes. Thus the WRR hashigher production per unit area than the SWR over monthlytimescales, but total production is similar over annual time-scales (Plate 7 and Table 3). High chlorophyll (phytoplanktonbiomass) and growth during all seasons (in most regions) resultin a high mean annual production within the MCR of 528.8 gCm2 yr21, which accounts for 9.2% of total SO production butonly 2.4% of the area (Plate 7 and Table 3). The bulk ofprimary production comes from the midlatitude regions, withareas poleward of 508S accounting for only 20.1% of totalprimary production while occupying 42.2% of the total area(Table 3). This reflects a shorter growing season at high lati-tudes, which is a function of strong light limitation duringwinter months. Total primary production in Antarctic SurfaceWaters, i.e., areas from the PF south to Antarctica, is 1.42 GtC yr21 from a maximum area of 30.74 million km2 (Table 3:WRR 1 SIZ 1 POOZ 1 PFR).

5. DiscussionThe patterns in chlorophyll distribution described here are

qualitatively similar to those of previous studies of the SO withthe CZCS sensor [Sullivan et al., 1993; Comiso et al., 1993].There are some notable differences, most likely due to thesparse CZCS coverage in this region. Extensive phytoplanktonblooms were observed in the southeast Pacific sector duringDecember 1997 (Plate 1b). No blooms were seen in this regionin the CZCS data, and silica limitation was suggested as apossible cause [Sullivan et al., 1993; Comiso et al., 1993]. Silicalimitation or perhaps iron limitation may account for the lackof blooms here in January and February (Plate 1). The plumeof elevated chlorophyll values extending downstream from theKerguelen Plateau (beginning at ;708E; Plate 1b) was largerthan observed previously [Sullivan et al., 1993; Comiso et al.,1993]. The bloom in the southern Weddell Sea (Plate 1b) wasmuch larger and extended farther west than was observed withthe CZCS, likely because of the unusually strong summer icemelt during this season [Sullivan et al., 1993; Comiso et al.,1993; Comiso and Gordon, 1998].

At high latitudes (.508S), maximum production was esti-mated within the WRR at 1.39 gC m22 d21 during December1997, with an annual production of 156 gC m22 yr21 (Table 3).Several studies have measured primary production on the RossSea shelf at rates .1.0 gC m22 d21 [Smith et al., 1996; Bates etal., 1998]. Nelson et al. [1996] combined in situ data fromseveral seasons to estimate an annual primary production onthe Ross Sea shelf of 142 gC m22 yr21. The modeling study ofArrigo et al. [1998] used CZCS chlorophyll concentrations (cor-rected with the SOP algorithm) to estimate primary productionof 3.94 and 1.44 gC m22 d21 for the Ross and Weddell shelfareas, respectively, during December. By combining all shelfareas for the months of December and January, they estimatedthe average production to be ;1.5 gC m22 d21 [Arrigo et al.,1998].

Wefer and Fischer [1991] estimated annual primary produc-tion in the Polar Front Zone to be 83 gC m22 yr21 on the basisof sediment trap data in the Atlantic sector, similar to our PFRestimate of 82.0 gC m22 yr21 (Table 3). For the combinedPOOZ and SIZ regions they estimated annual primary pro-duction to be 21.5 gC m22 yr21 [Wefer and Fischer, 1991]. Thisis considerably less than our estimates of 62.3, 54.2, and 50.8gC m22 yr21 for the POOZ, MIZ, and SIZ, respectively (Table3). If nonproductive waters are included in calculating area-normalized production (total production divided by maximumSIZ extent; Table 2), mean SIZ production drops to 29.1 gCm22 yr21 (Table 3). Arrigo et al. [1998] estimated annual pri-mary production to be ;130 gC m22 in pelagic waters (.508S),;141 gC m22 for the MIZ, and ;184 gC m22 for shelf waters(annual mean production calculated from Arrigo et al. [1998,Table 3] using our method 1).

Comparisons between our MIZ values and those of Arrigo etal. [1998] are difficult because of the different definitions usedin defining this region. Different percentage ice cover cutoffswere used, and in addition, we excluded the high biomass areasof the southern Weddell and Ross Seas (the WRR) from ourMIZ region. The maximum estimated MIZ production ratesduring January was 0.336 gC m22 d21 (see Plate 7). This isconsiderably lower than the rates estimated by Arrigo et al.[1998] and the estimates of Smith and Nelson [1986] of 0.571gC m22 d21 for the Weddell Sea and 0.962 gC m22 d21 for theRoss Sea based on in situ measurements. Our estimate of


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annual total MIZ production (0.10 Gt C; Table 3) is alsoconsiderably less than previous estimates (0.38 Gt C [Smithand Nelson, 1986] and 0.41 Gt C [Arrigo et al., 1998]). Our totalSIZ production was 0.472 Gt C (Table 3).

Several factors could account for the differing estimates ofMIZ productivity. The differing definitions for the MIZ re-sulted in larger areal extent in both of these other studies.Maximum MIZ extent (during December) was 6 [Arrigo et al.,1998] and 6.84 million km2 [Smith and Nelson, 1986], while ourvalue was 5.5 million km2. We excluded the high-productivityWRR from our MIZ areas. If WRR areas are not excluded,our total MIZ production is increased to 0.114 Gt C. Smith andNelson [1986] used the average of the Weddell and Ross Sea insitu measurements to calculate total production. These areashad the strongest ice edge blooms during the 1997–1998 seasonand much higher chlorophyll values than in other areas of iceretreat (Plates 1 and 2). Thus applying a production meancomputed from these areas may overestimate production else-where. Mean MIZ production during December in the Wed-dell Sea (0–708W, not excluding WRR areas) was 0.744 gCm22 d21, comparable to the Smith and Nelson [1986] estimatesbut more than twice our average for the whole MIZ during thismonth. Mean MIZ production in the Ross Sea (1608E–1408W,not excluding WRR areas) was 0.401 gC m22 d21. Thus spatialand interannual variability could be important factors. A thirdfactor that may be relevant is the use of SST to estimate localmaximum production rates in the VGPM. The regression ofPopt

B versus temperature of Behrenfeld and Falkowski [1997]may underestimate maximum production rates in cold ice edgesurface waters of the Antarctic as samples of these waters areminimally represented in their in situ data set.

Our estimate for total primary production at latitudes .308Swas 14.2 Gt C yr21 (Table 3). Longhurst et al. [1995] estimatedprimary production within different regions of the global oceanusing CZCS data (GP algorithm) combined with a primaryproduction model. The total production within the four SOregions was 8.2 Gt C yr21 [Longhurst et al., 1995]. This totaldoes not include coastal production or the production frommid-ocean gyre regions below 308S. Adding production fromthese other regions, after multiplying by the approximate frac-tion, which is below 308S, increases the total to ;11.2 Gt Cyr21 [Longhurst et al., 1995, Figure 2, Table 2].

Our estimated total primary production for all areas at lat-itudes .5508S was 2.9 Gt C yr21 (Table 3). Longhurst et al.[1995] estimated total production of 2.24 Gt C yr21 for theirAntarctic and Antarctic Polar regions. These regions accountfor most of the area below 508S. If primary production fromhalf of their Subantarctic region is added (approximate portionbelow 508S), the total is increased to 4.01 Gt C yr21 [Longhurstet al., 1995]. Arrigo et al. [1998] estimated production for allwaters .508S at 4.4 Gt C yr21 on the basis of total pigments(with the SOP correction to CZCS data), with lower estimatesof 3.24 and 3.95 Gt C yr21 after correcting for phaeopigments,which were not distinguishable from chlorophyll with theCZCS. A recent run of the VGPM model using the SOPalgorithm corrections for the CZCS data and correcting for seaice cover gave an annual production of 2.9 Gt C yr21 (M.Behrenfeld, personal communication, 1999).

These model estimates are heavily dependent on the satel-lite surface chlorophyll concentrations used. If SeaWiFS un-derestimates surface chlorophyll concentrations, our estimateof primary production would be too low. Alternatively, as dis-cussed in section 4.1, the SOP algorithm may have overesti-

mated chlorophyll concentrations over much of the SO. If so,estimates based on these chlorophyll concentrations would betoo high. The model of Arrigo et al. [1998] was based on thesatellite data and the available nitrate and silicic acid but didnot allow for iron limitation of phytoplankton growth rates.This likely leads to overestimates of production, particularly inopen ocean waters [see Moore et al., 2000, and referencestherein].

The satellite-based estimates can be compared with esti-mates that extrapolate from a limited number of in situ obser-vations. This approach lacks the high spatial coverage of thesatellite data. Smith [1991] estimated total production south ofthe PF at 1.23 Gt C. Priddle et al. [1998] estimated productionsouth of the SAF at ;1.7 Gt C yr21, or ;30–40 g C22 yr21, onthe basis of estimates of carbon consumption by top levelpredators and the production needed to support it and onseasonal nutrient drawdown at several locations. These meth-ods may have underestimated total production. Extrapolationfrom a limited number of locations is unlikely to be accurategiven the large degree of regional and latitudinal variabilitydemonstrated in this paper. In their food web model, Priddle etal. [1998] did not allow for direct sinking of diatoms out of thesurface layer, which may be an important loss process andwould increase production estimates. Estimates based on nu-trient drawdown may underestimate production because ofrecycling within the surface layer.

Seasonal variations of atmospheric oxygen concentrationscan be used to estimate large-scale oceanic production andglobal-scale carbon sinks [Keeling et al., 1993; Bender et al.,1996]. Our total production estimates (scaled by appropriate fratios) can be compared with these atmospheric-based esti-mates of seasonal net production. Bender et al. [1996] exam-ined seasonal O2/N2 ratios in the Southern Hemisphere andargued that a seasonal minimal net oceanic production of;2.6–3.6 molC m22 yr21 was required to account for theseasonal atmospheric O2 variations based on the model resultsof Keeling et al. [1993]. This represents a seasonal net produc-tion in temperate latitudes of ;31.2–43.2 gC m22, with a meanof ;36 gC m22 [Keeling et al., 1993; Bender et al., 1996]. Thetemperate band of Keeling et al. [1993] consisted of latitudesfrom 23.68 to 44.48S. Total ocean area over this band is;6.598 3 1013 m2. Thus the net production estimates ofBender et al. [1996] represent a total seasonal net productionover this band of (6.598 3 1013) 3 36 5 2.37 3 1015 gC, or 2.37Gt C. This is a rough estimate that ignores latitudinal mixing inthe atmosphere across bands. However, such mixing is limited,as evidenced by the much weaker seasonal cycle in oxygen atlow latitudes and the opposite phasing of the seasonal cycles inthe Northern and Southern Hemispheres [Keeling et al., 1998].

The mean Southern Hemisphere seasonal cycle in atmo-spheric O2 increases over the 4 month period October–January, with an amplitude of ;70 per meg, and is largely theresult of oceanic processes below 308S [Keeling et al., 1998].Approximately 81% of the seasonal cycle at midlatitudes is dueto net oceanic production [Keeling et al., 1993]. A similar sea-sonal amplitude in oxygen is seen at the South Pole [Keeling etal., 1998]. Of the 3 years examined by Bender et al. [1996] the1993–1994 season most closely resembled the long-term meancycle at southern midlatitudes [see Keeling et al., 1998]. The1997–1998 seasonal atmospheric oxygen cycle was nearly iden-tical to the mean pattern of Keeling et al. [1998] (R. Keeling,personal communication, 1999). The 1993–1994 estimate forminimal net oceanic production by Bender et al. [1993] was 36


gC m22, which, as calculated above, would imply a seasonal netoceanic production of 2.37 Gt C. On the basis of several con-siderations, Bender et al. [1993] argued that actual oceanic netproduction was higher than their minimum estimates by afactor of ;1.5. This net production would increase the total netproduction estimate to 3.56 Gt C. Can our estimated primaryproduction at latitudes below 308S account for a seasonal netproduction of 2.37–3.56 Gt C over the October 1997 to January1998 period?

Our estimated total primary production for the area 308–608S over the 4 month period October 1997 through January1998 was 6.2 Gt C or 71.4 gC m22. The seasonal net productionimplied by the atmospheric O2 data would then represent an fratio (the ratio of new to total production) in the range of0.38–0.57. Typical f ratios for these mainly Subantarctic watersrange from 0.3 to 0.5 [Banse, 1996]. Seasonal net productioncan exceed short-term estimates of new production for a num-ber of reasons [see Bender et al., 1996]. Seasonal net produc-tion can have high f ratios relative to annual new productionbecause some of the organic C formed but not respired duringspring/summer months is respired later in the season. In addi-tion, some fixed organic matter sinks and is respired below thesurface mixed layer (but still in the euphotic zone) and thusmight not influence spring/summer O2 outgassing. Thus, takingthese factors into account, primary production in SO midlati-tude waters is sufficient to account for the observed seasonalcycle in atmospheric O2 documented previously [Bender et al.,1996; Keeling et al., 1998].

SeaWiFS data are providing the most comprehensive lookyet at the distribution of chlorophyll in the SO. Several othersatellite ocean color sensors are scheduled to go into orbit overthe next decade. Thus SeaWiFS is laying the baseline for along-term continuous time series of global surface chlorophyllmeasurements. Combining satellite data with ocean circula-tion, climate, and biogeochemical models will provide valuabletools to improve our understanding of the ocean ecosystemsand the global carbon cycle.

Acknowledgments. The authors would like to thank Dave Nelson,Jim Richman, Ted Strub, and Ricardo Letelier for helpful commentsand suggestions. The authors would also like to thank the SeaWiFSproject (code 970.2) and the Distributed Active Archive Center (code902) at the Goddard Space Flight Center, Greenbelt, MD 20771, forthe production and distribution of the ocean color data, respectively.These activities are sponsored by NASA’s Earth Science EnterpriseProgram. We would also like to thank the EOS Distributed ActiveArchive Center (DAAC) at National Snow and Ice Data Center (Boul-der, CO) for the sea ice data, the National Center for EnvironmentalPrediction for the interpolated SST data, and the SeaWiFS project forproviding the surface radiation data. This work was funded by a NASAEarth System Science Fellowship (J.K.M.) and by NASA/EOS grantNAGW-4596 (M.R.A.).

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the western Ross Sea, Science, 266, 261–263, 1994.Arrigo, K. R., C. R. McClain, J. K. Firestone, C. W. Sullivan, and J. C.

Comiso, A comparison of CZCS and in situ pigment concentrationsin the Southern Ocean, NASA Tech. Memo., 104566, 30–34, 1994.

Arrigo, K. R., D. Worthen, A. Schnell, and M. P. Lizotte, Primaryproduction in Southern Ocean Waters, J. Geophys. Res., 103, 15,587–15,600, 1998.

Banse, K., Low seasonality of low concentrations of surface chlorophyllin the Subantarctic water ring: Underwater irradiance, iron, or graz-ing?, Prog. Oceanogr., 37, 241–291, 1996.

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bution of CO2 species, estimates of net community production, andair-sea CO2 exchange in the Ross Sea polynya, J. Geophys. Res., 103,2883–2896, 1998.

Behrenfeld, M. J., and P. G. Falkowski, Photosynthetic rates derivedfrom satellite-based chlorophyll concentration, Limnol. Oceanogr.,42, 1–20, 1997.

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(Received August 16, 1999; revised July 19, 2000;accepted July 26, 2000.)


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